@article{84ce03ec2c094aa7ab1a6972f5a7d524,
title = "Towards Process-based Range Modeling of Many Species",
abstract = "Understanding and forecasting species{\textquoteright} geographic distributions in the face of global change is a central priority in biodiversity science. The existing view is that one must choose between correlative models for many species versus process-based models for few species. We suggest that opportunities exist to produce process-based range models for many species, by using hierarchical and inverse modeling to borrow strength across species, fill data gaps, fuse diverse data sets, and model across biological and spatial scales. We review the statistical ecology and population and range modeling literature, illustrating these modeling strategies in action. A variety of large, coordinated ecological datasets that can feed into these modeling solutions already exist, and we highlight organisms that seem ripe for the challenge.",
keywords = "data fusion, ecological forecasting, hierarchical model, inverse modeling, species distribution models",
author = "Evans, {Margaret E.K.} and Cory Merow and Sydne Record and McMahon, {Sean M.} and Enquist, {Brian J.}",
note = "Funding Information: The authors benefitted from discussions surrounding an Organized Oral Session titled {\textquoteleft}Novel Approaches for Process-Based Species Distribution Models{\textquoteright} at the 2014 annual meeting of the Ecological Society of America, and a workshop {\textquoteleft}Ecological insights from integrating diverse data with hierarchical models{\textquoteright} sponsored by the Berkeley Initiative on Global Change Biology in October, 2014. In particular, the authors gratefully acknowledge discussions with Tom Miller, Rob Salguero-G{\'o}mez, Mark Vanderwel, Matt Talluto, Jorn Pagel, Frank Schurr, Katy Prudic, Andrew Rominger, Dominic LaRoche, Regis Ferriere, Kent McFarland, Dave Moore, Jeff Oliver, and Noah Charney. John Shaw (Interior West-Forest Inventory and Analysis, USDA Forest Service) and Andrew Gray (Pacific Northwest-Forest Inventory and Analysis, USDA Forest Service) provided data on the abundance of U.S.A. tree species. We thank Ben Olimpio for his assistance producing panel (B) in Box 2 . MEKE acknowledges the support of NSF grant DEB-1632706 and USDA-AFRI grant 2016-67003-24944 . CM acknowledges funding from USDA-NRI grant 2008-35615-19014 and DEB-1137366 . SMM and CM acknowledge funding support from NSF DEB-1137366 and Smithsonian Institution's Center for Tropical Forest Science-Forest Global Earth Observatory . BJE acknowledges support from a fellowship from the Aspen Center for Environmental Studies and from NSF DBI-ABI 1565118 . Publisher Copyright: {\textcopyright} 2016 Elsevier Ltd",
year = "2016",
month = nov,
day = "1",
doi = "10.1016/j.tree.2016.08.005",
language = "English (US)",
volume = "31",
pages = "860--871",
journal = "Trends in Ecology and Evolution",
issn = "0169-5347",
publisher = "Elsevier Limited",
number = "11",
}